Adaptive artificial neural network for uncertainty propagation
Papers|更新时间:2025-08-22
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Adaptive artificial neural network for uncertainty propagation
不确定性传播的自适应人工神经网络
“In the field of uncertainty propagation, this study introduces its research progress. Expert proposed a novel adaptive UP method based on the artificial neural network (ANN), which provides solutions to solve the problem of accurate and efficient UP in engineering applications.”
Journal of Reliability Science and EngineeringVol. 1, Issue 1, Pages: 50-79(2025)
作者机构:
Institute for Risk and Reliability, Leibniz Universität Hannover, Hannover 30167, Germany
School of Mathematics and Statistics, Northwestern Polytechnical University, Xi'an 710072, People's Republic of China
Department of Civil and Environmental Engineering, University of Liverpool, Liverpool L69 3BX, United Kingdom
International Joint Research Center for Resilient Infrastructure & International Joint Research Center for Engineering Reliability and Stochastic Mechanics, Tongji University, Shanghai 200092, People's Republic of China
作者简介:
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"Yan Shi received the B.E. degree and PhD degree in School of Aeronautics from Northwestern Polytechnical University, Xi'an, China. He is currently an Alexander von Humboldt Fellow at Institute for Risk and Reliability, Leibniz Universität Hannover. His research interests include structural/system/network reliability analysis, sensitivity analysis, design optimization, and machine learning techniques."
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"Lizhi Niu received the B.S. degree and M.S degree from School of Mathematics and Statistics from Northwestern Polytechnical University, Xi'an, China, and he is a dual PhD candidate in School of Mathematics and Statistics from Northwestern Polytechnical University, Xi'an, China, as well as department of Engineering from University of Palermo, Palermo, Italy. His research interests include probability response of stochastic dynamic system, stochastic reliability analysis, integral transform and fractional calculus."
]
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"Michael Beer received the M.S. degree and PhD degree in Civil Engineering from Technische Universität Dresden (TU Dresden), Dresden, Germany. He is a Full Professor and Head of the Institute for Risk and Reliability at Leibniz Universität Hannover. He is also part time Professor of the Institute for Risk and Uncertainty at University of Liverpool, and Guest Professor of the International Joint Research Center for Resilient Infrastructure & International Joint Research Center for Engineering Reliability and Stochastic Mechanics at Tongji University. He mainly focuses on efficient stochastic analysis of engineering systems and structures, including response characterization, reliability analysis, sensitivity analysis, and robust and reliability-based design optimization."
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Yan Shi, Lizhi Niu and Michael Beer. Adaptive artificial neural network for uncertainty propagation[J]. Journal of Reliability Science and Engineering, 2025, 1: 015002.
Yan Shi, Lizhi Niu and Michael Beer. 不确定性传播的自适应人工神经网络[J]. 可靠性科学与工程学报(英文), 2025, 1: 015002.
Yan Shi, Lizhi Niu and Michael Beer. Adaptive artificial neural network for uncertainty propagation[J]. Journal of Reliability Science and Engineering, 2025, 1: 015002. DOI: 10.1088/3050-2454/ada036.
Yan Shi, Lizhi Niu and Michael Beer. 不确定性传播的自适应人工神经网络[J]. 可靠性科学与工程学报(英文), 2025, 1: 015002. DOI: 10.1088/3050-2454/ada036.
Adaptive artificial neural network for uncertainty propagation